On the asymptotic power of a goodness-of-fit test based on a cumulative Kullback–Leibler discrepancy

We discuss a goodness-of-fit test arising from information-theoretical considerations. We show that, for a simple null hypothesis, our test has superior asymptotic power compared to the Anderson–Darling test when the alternative lies in a certain large class of distribution functions.